At present, the use of sensors in electronic devices and most notably on smartphones and digital tablets is becoming more and more common and one can safely state will soon become commonplace in any electronic device.
Usually, these sensors range from motion sensors, such as magnetometers, accelerometers (the compass function in an electronic device is a combination of magnetometer and accelerometer data) and gyros (providing info about rotation speed) to environmental and biosensors like air pressure sensors and also proximity sensors.
By utilising sensors in accessories for a portable terminal, such as for a mobile terminal, an application or cloud service could be provided with information about the user that is more cumbersome to achieve with other devices, since accessories can be designed to be attached to the user's body, e.g. headsets, bracelets, smart clothes etc. Especially, having motion and direction sensors in a headset would significantly improve many use cases by providing information on how the user is moving the head and what direction the user is facing. This information can not be provided by the portable terminal itself.
Sensors that are feasible in accessories are mainly of the MEMS (Microelectromechanical Systems) type.
However, in order to ensure safe correct functioning of these MEMS sensors several problems need to be overcome.
In the case of the compass, which is a combination of a magnetometer and an accelerometer, it gives an absolute heading (north) but is quite sensitive to magnetic disturbances. Calibration is done to compensate for local magnetic disturbances. The disturbances can be internally in the device (mobile terminal or accessory) or from iron in the surroundings (cars, the office chair . . . ). In a mobile terminal, the calibration of the compass is currently done by asking the user to move the phone in a known pattern, often like the digit eight, which is not practical when the compass is in e.g. a headset.
With regards to initialisation of Inertial Navigation Systems (INS) where one needs to be able to calculate the movement (distance) of the user utilizing the INS, the sensor data needs to be integrated twice, since the data is supplied by an accelerometer. In this context, noise and drift in the sensor signal will cause an integration error increasing with time. Therefore, the integration algorithms need to be occasionally reset when the electronic device or mobile terminal using the INS is in a known position.
Also, when evaluating data from a gyro one needs to compensate for drift in the rotation measurement data from the sensor. As is known in the art, a gyro usually gives an output in terms of degrees per second. Thus, to get the actual rotation (in degrees), the output from the gyro must be integrated with respect to time. Hence the algorithm must be occasionally reset in a known direction.
There is therefore a need for a more simple, efficient and cost-effective way of overcoming the initialization and calibration problems encountered with sensors which use known technology, especially in the context of accessories for mobile or portable terminals.
Moreover, it would be advantageous to provide a new and simpler way of recalibrating sensors and sensor functionality in mobile terminals which use data from two or more sensors, such as from the compass or the INS function in the mobile terminal.